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A novel Approach for Non-Invasive Lung Imaging and Targeting Lung Immune Cells.

ABSTRACT: Despite developments in pulmonary radiotherapy, radiation-induced lung toxicity remains a problem. More sensitive lung imaging able to increase the accuracy of diagnosis and radiotherapy may help reduce this problem. Super-paramagnetic iron oxide nanoparticles are used in imaging, but without further modification can cause unwanted toxicity and inflammation. Complex carbohydrate and polymer-based coatings have been used, but simpler compounds may provide additional benefits. Herein, we designed and generated super-paramagnetic iron oxide nanoparticles coated with the neutral natural dietary amino acid glycine (GSPIONs), to support non-invasive lung imaging and determined particle biodistribution, as well as understanding the impact of the interaction of these nanoparticles with lung immune cells. These GSPIONs were characterized to be crystalline, colloidally stable, with a size of 12 ± 5 nm and a hydrodynamic diameter of 84.19 ± 18 nm. Carbon, Hydrogen, Nitrogen (CHN) elemental analysis estimated approximately 20.2 × 10³ glycine molecules present per nanoparticle. We demonstrated that it is possible to determine the biodistribution of the GSPIONs in the lung using three-dimensional (3D) ultra-short echo time magnetic resonance imaging. The GSPIONs were found to be taken up selectively by alveolar macrophages and neutrophils in the lung. In addition, the GSPIONs did not cause changes to airway resistance or induce inflammatory cytokines. Alveolar macrophages and neutrophils are critical regulators of pulmonary inflammatory diseases, including allergies, infections, asthma and chronic obstructive pulmonary disease (COPD). Therefore, pulmonary Magnetic Resonance (MR) imaging and preferential targeting of these lung resident cells by our nanoparticles offer precise imaging tools, which can be utilized to develop precision targeted radiotherapy as well as diagnostic tools for lung cancer, thereby having the potential to reduce the pulmonary complications of radiation.

SUBMITTER: Chakraborty A

PROVIDER: S-EPMC7084491 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PURPOSE:Hyperprogression is an atypical response pattern to immune checkpoint inhibition that has been described within non-small cell lung cancer (NSCLC). The paradoxical acceleration of tumor growth after immunotherapy has been associated with significantly shortened survival, and currently, there are no clinically validated biomarkers to identify patients at risk of hyperprogression. EXPERIMENTAL DESIGN:A total of 109 patients with advanced NSCLC who underwent monotherapy with Programmed cell death protein-1 (PD1)/Programmed death-ligand-1 (PD-L1) inhibitors were included in the study. Using RECIST measurements, we divided the patients into responders (n=50) (complete/partial response or stable disease) and non-responders (n=59) (progressive disease). Tumor growth kinetics were used to further identify hyperprogressors (HPs, n=19) among non-responders. Patients were randomized into a training set (D1=30) and a test set (D2=79) with the essential caveat that HPs were evenly distributed among the two sets. A total of 198 radiomic textural patterns from within and around the target nodules and features relating to tortuosity of the nodule associated vasculature were extracted from the pretreatment CT scans. RESULTS:The random forest classifier using the top features associated with hyperprogression was able to distinguish between HP and other radiographical response patterns with an area under receiver operating curve of 0.85±0.06 in the training set (D1=30) and 0.96 in the validation set (D2=79). These features included one peritumoral texture feature from 5 to 10 mm outside the tumor and two nodule vessel-related tortuosity features. Kaplan-Meier survival curves showed a clear stratification between classifier predicted HPs versus non-HPs for overall survival (D2: HR=2.66, 95% CI 1.27 to 5.55; p=0.009). CONCLUSIONS:Our study suggests that image-based radiomics markers extracted from baseline CTs of advanced NSCLC treated with PD-1/PD-L1 inhibitors may help identify patients at risk of hyperprogressions.

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A novel Approach for Non-Invasive Lung Imaging and Targeting Lung Immune Cells.

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